LABORATORY OF STATISTICS FOR INTERNATIONAL MARKETS ANALYSIS

Academic year
2022/2023 Syllabus of previous years
Official course title
LABORATORY OF STATISTICS FOR INTERNATIONAL MARKETS ANALYSIS
Course code
EM1069 (AF:358711 AR:187337)
Modality
On campus classes
ECTS credits
6
Degree level
Master's Degree Programme (DM270)
Educational sector code
SECS-S/01
Period
3rd Term
Course year
2
Where
TREVISO
Moodle
Go to Moodle page
The course aims at equipping the students with the statistical tools most suitable for the evaluation of international markets, starting from economic, financial, socio-economic and institutional data which are relevant for firms decisions.
The students, at the end of the course should learn:
- which are the data sources relevant for the international market aalysis
- how to browse within these data sources
- build up a database integrating different sources
- analyse the database to profile foreign Countries in terms of risks/opportunities for firms
- Basic knowledge of statistics and probability (with particular reference to multiple regression)
- basic knowledge of R
- Relevant data sources for international market analysis
- Downloading the data from different sources and managing the data
- data cleaning: statistical tools for the analysis and replacement of missing data
- selection of the relevant variables through Lasso regression
The main referral text for statistical methods is:
Gareth, James, et al. An introduction to statistical learning: with applications in R. Spinger, 2013.

Class notes, commented R scripts and other materials will be uploaded in the moodle page of the course
The exam will consist in the writing of a report in which the students will analyze, through R, the international markets offering the best opportunities for a specific industrial sector.
The size and composition of working groups will depend on the number of students attending the course.
Interactive, hands-on approach: lectures and R lab sessions will follow a leading case study
English
oral
Definitive programme.
Last update of the programme: 15/09/2022